The field of this invention is classification of rodent vocalizations. One embodiment automatically examines many vocalizations and identifies common patterns. Another embodiment automatically associates vocalizations with known body behaviors. Yet another embodiment automatically associates vocalizations as either “positive” or “negative.” Yet another embodiment automatically associates vocalizations with previously known phenotypes, such as disease-positive or disease-negative behaviors. Yet another embodiment automatically associates vocalizations as occurring prior to, with, or after known body behaviors, generating behavioral “phrases.” Yet another embodiment combines vocalization with other observed and known behaviors to identify, classify or correlate behaviors based on merged vocalizations and visual behaviors. Yet another embodiment associates vocalizations, optionally combined with other behaviors, to identify cognitive, emotional, or other “thinking” states of rodents.
An environment for embodiments is typically a vivarium with rodents in cages, where cages are equipped with individual audio—usually ultrasonic—sensors and vision sensors such as cameras. Other sensors may be used, such as temperature, air chemistry, animal scales, RFID, and the like. A vision system may identify other animal phenotype elements, such a respiration rate, respiration quality, heart rate, and other stand-alone behaviors, behavioral phrases, or longer-term behaviors.
Both mice and rates generate frequent and complex vocalizations, often in the ultrasonic range, such as around 22 KHz or 50 KHz.
Understanding vocalizations and their relationship to known or new behaviors adds significantly the value of vivarium-based studies such as drug efficacy, and characterization of animal types.
Continuous data recording of both ultrasonic vocalizations and vision-based activity, in an animals' home cage, with subsequent automated multi-dimensional analysis of both data types, provides improvement over the prior art.